3 citations · 5 across the 4 of their papers we have counts for
4 papers · 1 filter
Separate-and-Detect: Unified Drum Transcription and Stem Generation via Latent Diffusion
Wei-Han Hsu, Chih-Cheng Chang, Bo-Yu Chen +2
Automatic Drum Transcription (ADT) is commonly formulated as a direct mapping from a music mixture to symbolic drum events. While effective for transcription, this formulation disc…
Audio Prompt Adapter: Unleashing Music Editing Abilities for Text-to-Music with Lightweight Finetuning
Fang-Duo Tsai, Shih-Lun Wu, Haven Kim +3
Text-to-music models allow users to generate nearly realistic musical audio with textual commands. However, editing music audios remains challenging due to the conflicting desidera…
JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion Models
Peike Li, Boyu Chen, Yao Yao +3
Music generation has attracted growing interest with the advancement of deep generative models. However, generating music conditioned on textual descriptions, known as text-to-musi…
Exploiting Pre-trained Feature Networks for Generative Adversarial Networks in Audio-domain Loop Generation
Yen-Tung Yeh, Bo-Yu Chen, Yi-Hsuan Yang
While generative adversarial networks (GANs) have been widely used in research on audio generation, the training of a GAN model is known to be unstable, time consuming, and data in…